\begin{abstract}
This paper concerns the problem of multi-category RFID estimation: given a set of RFID tags, we want to quickly and accurately estimate the number of tags in each category.
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To the best of our knowledge, there is no dedicated effort on our multi-category RFID estimation problem.
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In this~paper, we propose a protocol called Simultaneous Estimation for Multi-category RFID systems (SEM).
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We use $\mbox{single-one}$ Manchester coding, which is supported by the ISO $\mbox{18000-6}$ RFID standard, to encode category IDs.
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To achieve the guaranteed accuracy, we first calculate the variance of our estimator for one round and the variance of the average estimate in multiple rounds.
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To find the optimal frame size, we propose an efficient binary search-based algorithm.
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To~address significant variance in category~sizes, we propose an Adaptive Partitioning (AP) strategy to group categories of similar sizes together and execute our estimation protocol for each group separately.
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Compared with the approach of estimating each category separately using prior RFID estimation schemes, our protocol is much faster.
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For example, with 50 categories, our protocol is about ten times faster than prior estimation schemes.
\end{abstract}

\category{C.2.1}{Computer-Communication Networks}{Network Architecture and Design-Wireless communication}
\vspace{-0.1in}
\terms{Algorithms, Design, Performance, Experimentation}
\vspace{-0.1in}
\keywords{RFID, Cardinality Estimation, Multiple Categories} 